The Path to a Driverless Future
Autonomous Vehicle Design Challenges
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Autonomous Vehicle Design Challenges
Spanning the Gap
There have been remarkable advances in driver assistance technology over the
past few years, bringing features such as active automatic parking, cruise control,
and emergency braking to consumer vehicles. However, there’s still a large gap
between current systems and systems that will make driverless cars practical and
affordable for the general public. Some of the challenges that must be overcome
involve on-board electronic systems and building a reliable, secure wireless
infrastructure—and the cloud-based services it will support.
One of the most challenging technical issues will be developing a sensor system
that can accurately gauge road conditions and identify potential hazards during
inclement weather, such as rain, snow or fog. While multi-spectral imaging may
help pierce the visual clutter created by adverse meteorological conditions,
snowfall can change the shape of familiar objects and even the shape of the road
itself. This makes it much harder for a vehicle’s on-board intelligence to recognize
potential obstacles like snow piles, which may completely alter the shape of the
road.
An all-weather autonomous vehicle (AV) must be able to adapt gracefully when
one or more of its sensors gets covered by mud, slush or other debris thrown up
from the road. Designers will also need to teach vehicles to recognize and react to
subtler hazards like black ice and deep puddles, which can be hard for humans to
recognize, let alone an on-board artificial intelligence (AI) system.
Securing the Future
Security has already become an issue for today’s digitally-enabled vehicles and will
pose even bigger design issues in autonomous vehicles. Hackers have
demonstrated that many cars and trucks can provide unauthorized access to
critical subsystems through vehicles’ wireless key systems, Bluetooth, Wi-Fi links,
and even radio-readable tire pressure monitoring systems. Connected telematics
services, such as GM’s OnStar, Toyota’s Safety Connect, and Ford’s SYNC, also use
cellular or Wi-Fi connections that offer a potential access point for mischief-
makers. A recent study by Frost & Sullivan titled, “Key Trends Impacting the
Infotainment Market to 2020,” reports that connected telematics systems are the
preferred route of entry for hackers.
Autonomous Vehicle Design Challenges
These potential vulnerabilities (Figure 1) will nearly double in completely
autonomous vehicles, which have even more networked Electronic Control Units
(ECUs), sensors, and actuators connected to their vehicle busses. In addition, the
wireless cloud connections, which AVs use to access routing, traffic, and other vital
information, will present a tempting target unless they are hardened against cyber-
attacks. Vehicle-to-vehicle (V2V) communication links, which will make advanced
functions such as Cooperative Adaptive Cruise Control, Cooperative Forward
Collision Warning, and Vehicle-based Road Conditions and Pothole Warning
possible, must also be thoroughly secured. Even wired data connections, such as
diagnostic and maintenance ports and the USB interfaces used in a vehicle’s
entertainment systems, must also be designed to resist hijacking and unauthorized
use.
External Design Challenges
While these problems are being solved, work continues on the external resources
that AVs will need to freely navigate the public roadways.
Figure 1: Even today’s connected vehicles present multiple attack points which can be exploited by
hackers to do anything from remotely-controlling their entertainment systems to overriding the
driver’s inputs to the steering, braking, and engine controls. Image courtesy of Frost & Sullivan.
Autonomous Vehicle Design Challenges
This includes the cloud-based services that supply AVs with up-to-date navigation
data, routing information, and road condition alerts. These services will require a
robust wireless infrastructure to support them, as well as a series of standards-
based protocols which enable any AV to make use of them. Standards will also play
a critical role in Vehicle-to-Vehicle (V2V) communications, where a government-
backed 802.11p Wi-Fi standard called Wireless Access in Vehicular Environments,
or WAVE, enables data exchange between vehicles and the roadside infrastructure
that operates in the 5.9 GHz band of the wireless spectrum. WAVE, and its
associated protocols, will enable AVs to exchange data and cooperate with each
other. Among other things, WAVE will allow cars to cruise together efficiently,
avoiding many congestion-induced delays we experience today. They will also be
better able to warn each other of changing road conditions, upcoming hazards,
and impending problems with a vehicle that might disrupt the traffic flow.
Another top-priority external resource in development are the hyper-accurate
mapping databases and developing processes for maintaining them in near-real-
time. Humans can easily navigate using today’s mapping databases, which are only
accurate to within 10 to 20 feet, but an autonomous vehicle’s navigation system
requires resolutions of 10 to 20 centimeters to know precisely where the vehicle is
in relation to other cars, lane markers, pedestrians, and other roadway features.
Hyper-accurate maps will also contain the deep data features found in Google
Maps, which describes roadway features like no-left-turns, freeway on-ramps,
speed limits, and up-to-the-second traffic conditions. Once in place, the vehicles
using the system will help keep the database updated with real-time reports about
traffic and roadway conditions.
An Incremental Roll-Out
It’s likely that we won’t see a seamless hyper-map database that covers the entire
country or even an entire state immediately. Instead, the database will be built up
piecewise over a period of several years, and much like the deployment of cellular
networks, it’s likely that the efforts will be focused on urban areas first, followed
by highways and heavily-trafficked thoroughfares.
This could limit the areas where AVs can be used in a completely self-driving mode,
but many of their driver-assist features (collision avoidance, adaptive cruise
control, etc.) would still be available.
Autonomous Vehicle Design Challenges
During this transition period, self-driving cars can still find many applications.
Delivery and taxi services serving urban areas, for example, are expected to be
some of the first commercial applications for AVs.
One of the earliest experiments in short-range commercial AVs is the GATEway
project, which is developing so-called passenger pods that will be capable of
operating fully autonomously and safely on the streets of London. The system is
based on the existing Ultra PODS system currently in service at Heathrow Airport
(Figure 2). Operating at Terminal 5 for nearly five years, these pods have already
carried 1.5 million passengers and completed 3 million kilometers of fully
automated operation in a closed-course environment.
Conclusion
The shift to autonomous vehicles won’t happen overnight, nor will it occur as a
sudden shift to fully-autonomous operation. Instead, we’ll see today’s driver
assistance technologies becoming increasingly intelligent, capable, and able to
interact with the vehicle’s other subsystems and, eventually, other vehicles.
Today’s “dumb” cruise control systems, for example, will soon give way to
radar/LIDAR-based adaptive cruise control which automatically maintains proper
separation distance with the car ahead, matching speeds as necessary. The next
evolutionary step will be so-called cooperative cruise control systems that use V2V
communication to anticipate changes in traffic patterns as well as the vehicles
directly adjacent to them.
This punctuated evolutionary path will be repeated throughout the vehicle,
eventually enabling its subsystems to interact autonomously with each other,
other vehicles, and the cloud-based services that support them. In this manner,
designers will bring autonomous vehicles into commercial reality, one engineering
challenge at a time.
Figure 2: London's first autonomous vehicles
will be tested on the city's streets during the
summer of 2016. The vehicles used by the
system are based on the autonomous shuttle
pods already in operation at Heathrow Airport
(pictured). This deployment is part of the £8m
Gateway project (Greenwich Automated
Transport Environment) led by the UK's
Transport Research Laboratory (TRL).
Image courtesy of Ultra PRT.
Autonomous Vehicle Design Challenges
About the Author:
Lee Goldberg brings over 20 years' experience in technology reporting to his post as lead editor
at PD&D and MDT. Prior to entering the media realm, Lee was an electrical engineer. During that
time, he helped design microprocessors, embedded systems, renewable energy applications, and
the occasional interplanetary spacecraft.
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